Vehicle condition diagnosis control system and method
A VHM device according to embodiments of the present disclosure relates to a vehicle condition diagnosis control system and, more particularly, to a vehicle condition diagnosis control system and method which assess and deal with the condition of each component of a vehicle and, at the same time, accurately predict the replacement cycle of each consumable in such a way as to suit each vehicle or the driving pattern of each driver and provide the user periodic feedback about the overall condition of the vehicle.
1 . A vehicle health monitoring (VHM) device embedded in a vehicle, the VHM device comprising:
an interface configured to collect a plurality of pieces of raw data sensed from a data collection unit in the vehicle and to perform data transmission and reception to and from electric control units (ECUs) or a domain control unit (DCU);
a data selection unit configured to select sensing data required to diagnose the condition of a particular device or particular component of the vehicle from among the collected raw data;
a feature data generation unit configured to generate at least one piece of feature data having new features by linearly or nonlinearly combining the selected sensing data through a feature extraction algorithm;
a condition feature data derivation unit configured to derive condition feature data for the particular device or particular component by inputting the selected sensing data and the at least one piece of generated feature data into a machine learning-based condition diagnosis model; and
a control signal generation unit configured to generate a control signal for the particular device or particular component based on the condition feature data.
2 . The VHM device of claim 1 , further comprising a condition diagnosis model training unit configured to construct the condition diagnosis model by performing machine learning of a learning data set including at least either the selected sensing data, the at least one piece of generated feature data, or the feature characteristic data.
3 . The VHM device of claim 2 , wherein the condition feature data derivation unit is configured to derive the condition feature data based on sensing data weights assigned to respective pieces of the sensing data and feature data weights assigned to the at least one piece of feature data, and
wherein the feature data weights have a higher weight value than the sensing data weights.
4 . The VHM device of claim 2 , further comprising a feature data management unit which configures a condition feature data set by hierarchically structuring the condition feature data for each of a plurality of devices or components including the particular device or component.
5 . The VHM device of claim 4 , wherein the condition feature data set includes:
a first condition feature layer including the vehicle's chassis condition feature data, power condition feature data, and ADAS (advanced driver assistance systems) condition feature data;
a second condition feature layer including braking condition feature data, steering condition feature data, and suspension condition feature data, which is configured as lower-level data of the chassis condition feature data; and
a third condition feature layer including brake pad condition feature data, which is configured as lower-level data of the braking condition feature data.
6 . The VHM device of claim 5 , wherein the first condition feature data contained in the first condition feature layer is derived by additionally learning at least one piece of such data as the second condition feature data contained in the second condition feature layer and the third condition feature data contained in the third condition feature layer, and
the second condition feature data is derived by additionally learning at least one piece of such data as the third condition feature data.
7 . The VHM device of claim 5 , wherein, if the particular device or component is a brake pad, the selected sensing data includes brake pedal stroke data, vehicle deceleration data, master cylinder pressure data, tire pressure data, and weather data, the feature data includes brake pedal stroke-deceleration ratio data, and the condition feature data includes brake pad wear condition feature data, and
wherein the condition feature data derivation unit is configured to derive the brake pad wear condition feature data by assigning the highest weight value to the brake pedal stroke-deceleration ratio feature data based on road friction coefficient data estimated from the weather data.
8 . The VHM device of claim 7 , wherein the control signal generation unit is configured to adjust the gain of a braking force generated in response to the brake pedal stroke data based on the brake pad wear condition feature data.
9 . The VHM device of claim 7 , wherein the control signal generation unit is configured to adjust the timing for issuing a collision warning or the timing for entering an emergency braking mode based on the brake pad wear condition feature data.
10 . A vehicle condition diagnosis control system comprising:
a health monitoring (VHM) device embedded in a vehicle and configured to manage condition feature data for each device or each component by diagnosing the conditions of individual devices or components of the vehicle;
a data collection unit configured to collect sensing data from the devices or components and to transmit the same to the VHM device; and
a VHM cloud configured to cumulatively collect the sensing data and the condition feature data for each device or each component by performing periodical or non-periodical communication with the VHM device,
wherein the VHM device includes:
a data selection unit configured to select sensing data required to generate condition feature data for each device or component from among the collected sensing data;
a feature data generation unit configured to generate at least one piece of feature data having new features by linearly or nonlinearly combining the selected sensing data through a feature extraction algorithm;
a condition feature data derivation unit configured to derive condition feature data for each device or component by inputting the selected sensing data and the at least one piece of generated feature data into a machine learning-based condition diagnosis model; and
a control signal generation unit configured to generate a control signal for each device or component based on the condition feature data for each device or component.
11 . The vehicle condition diagnosis control system of claim 10 , wherein the VHM cloud includes:
a life prediction unit configured to derive life prediction data for each of the devices and components of the vehicle by inputting the cumulatively collected sensing data and the condition feature data for each device or component into a deep learning-based life prediction model; and
a complex condition feature data generation unit configured to generate the vehicle's complex condition feature data dependent upon the conditions of two or more devices or components by inputting the sensing data and the condition feature data for each device or component into a deep learning-based complex condition diagnosis model.
12 . The vehicle condition diagnosis control system of claim 11 , wherein the condition feature data derivation unit of the VHM device is configured to derive condition feature data for each device or component by inputting instantaneous values of the sensing data and instantaneous values of the at least one piece of feature data into the condition diagnosis model, and
wherein the life prediction unit and complex condition feature data generation unit of the VHM cloud are configured to derive the life prediction data and the complex condition feature data by inputting the sensing data accumulated in time series and the condition feature data for each device or component accumulated in time series into the life prediction model and the complex condition diagnosis model.
13 . The vehicle condition diagnosis control system of claim 11 , wherein, if the condition feature data for each device or component is out of a reference range, the VHM device periodically or non-periodically is configured to send the sensing data, the at least one piece of feature data, and the condition feature data for each device or component to the VHM cloud, and
wherein the VHM cloud is configured to generate a learning guidance data for training the condition diagnosis model through guidance based on the collected sensing data, the at least one piece of feature data, or the condition feature data for each device or component and then sends the same to the VHM device.
14 . The vehicle condition diagnosis control system of claim 11 , wherein the VHM cloud is configured to generate a vehicle management report based on the life prediction data and the complex condition feature data and then to send the same to the VHM device.